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  • Q&A: Relevant Search with Elasticsearch and Solr

    by David Iffland on  Sep 26, 2016 1

    In their book "Relevant Search", Doug Turnbull and John Berryman focus on the challenge of providing search results by balancing the needs and intents of the user. Using Elasticsearch and Solr, relevance engineers can constantly tune the needs of the business vs. the needs of the user.

  • Big Data Processing with Apache Spark - Part 5: Spark ML Data Pipelines

    by Srini Penchikala on  Sep 24, 2016 2

    With support for Machine Learning data pipelines, Apache Spark framework is a great choice for building a unified use case that combines ETL, batch analytics, streaming data analysis, and machine learning. In this fifth installment of Apache Spark article series, author Srini Penchikala discusses Spark ML package and how to use it to create and manage machine learning data pipelines.

  • Book Review: Site Reliability Engineering - How Google Runs Production Systems

    by João Miranda on  Sep 21, 2016

    "Site Reliability Engineering - How Google Runs Production Systems" is an open window into Google's experience and expertise on running some of the largest IT systems in the world. The book describes the principles that underpin the Site Reliability Engineering discipline. It also details the key practices that allow Google to grow at breakneck speed without sacrificing performance or reliability.

Spark GraphX in Action Book Review and Interview

Posted by Srini Penchikala on  Sep 12, 2016

InfoQ spoke with authors of Spark GraphX in Action book, Apache Spark framework and what's coming up in the area of graph data processing and analytics.

Chris Fregly on the PANCAKE STACK Workshop and Data Pipelines

Posted by Dylan Raithel on  Aug 29, 2016

InfoQ interviews Chris Fregly, organizer for the 4000+ member Advanced Spark and TensorFlow Meetup about the PANCAKE STACK workshop, Spark and building data pipelines for a machine learning pipeline

Christine Doig on Data Science as a Team Discipline

Posted by Srini Penchikala on  Aug 26, 2016

Christine Doig spoke at OSCON Conference about data science as a team discipline and how to navigate data science Python ecosystem. InfoQ spoke with Christine about challenges of data science teams.

Book Review and Excerpt: Infrastructure as Code

Posted by Abel Avram on  Jul 25, 2016

We review the book Infrastructure as Code by Kief Morris, who lays down the foundation for Infrastructure as Code and outlines the main patterns and practices recommended for building it.

Big Data Analytics with Spark Book Review and Interview

Posted by Srini Penchikala on  Jun 23, 2016

Big Data Analytics with Spark, authored by Mohammed Guller, provides a practical guide for learning Apache Spark. InfoQ and the author discuss the book & development tools for big data applications.

Big Data Processing with Apache Spark - Part 4: Spark Machine Learning

Posted by Srini Penchikala on  May 15, 2016

In this fourth installment of Apache Spark article series, author Srini Penchikala discusses machine learning concept & Spark MLlib library for running predictive analytics using a sample application.

The Holistic Approach: Preventing Software Disasters

Posted by Olivier Bonsignour on  Apr 28, 2016

Olivier Bonsignour on what "X-Raying" software means, how it can help prevent software disasters and why CIOs should care. 3

The Role of a Data Scientist in 2016

Posted by Ed Jones on  Mar 27, 2016

Data Science has been getting lot of attention as organizations are starting to use data analytics to gain insights into their data. This article takes a closer look at Data Scientist role in 2016.

Unified Data Modeling for Relational and NoSQL Databases

Posted by Allen Wang on  Feb 28, 2016

Current enterprise data architectures include NoSQL databases co-existing with RDBMS. In this article, author discusses a solution for managing NoSQL & relational data using unified data modeling. 5

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